Board committee meetings and firm financial performance : an investigation of Australian companies

This article examines how the frequency of board committee meetings impacts on Australian firms’ financial performance. Data were collected from 118 Australian listed companies – including 26 financial firms and 92 nonfinancial firms – for the period 1999–2007. Analysis of that data shows that the frequencies of audit committee meetings and remuneration committee meetings are positively and significantly associated with return on equity and return on assets. The frequencies of risk committee meetings do not show any significant effects on the financial performance of Australian firms. Estimated results are found to be robust after controlling for internal as well as external governance mechanisms that might affect Australian firm performance.

Family firms, board structure, political connections and performance: evidence from Bangladesh

This thesis provides critical empirical evidence on Bangladeshi family firm governance structures and their impacts on firm performance while taking political connections into consideration. Based on some theoretical argument the thesis presents some unique and robust results which are consistent with the Bangladeshi institutional characteristics.

Progress Toward Robust Polymer Hydrogels

In this review we highlight new developments in tough hydrogel materials in terms of their enhanced mechanical performance and their corresponding toughening mechanisms. These mechanically robust hydrogels have been developed over the past 10 years with many now showing mechanical properties comparable with those of natural tissues. By first reviewing the brittleness of conventional synthetic hydrogels, we introduce each new class of tough hydrogel: homogeneous gels, slip-link gels, double-network gels, nanocomposite gels and gels formed using poly-functional crosslinkers. In each case we provide a description of the fracture process that may be occurring. With the exception of double network gels where the enhanced toughness is quite well understood, these descriptions remain to be confirmed. We also introduce material property charts for conventional and tough synthetic hydrogels to illustrate the wide range of mechanical and swelling properties exhibited by these materials and to highlight links between these properties and the network topology. Finally, we provide some suggestions for further work particularly with regard to some unanswered questions and possible avenues for further enhancement of gel toughness.

A high performance position sensorless surface permanent magnet synchronous motor drive based on flux angle

A position sensorless Surface Permanent Magnet Synchronous Motor (SPMSM) drive based on flux angle is presented in this paper. The motor equations are written in rotor fixed d-q reference frame. A PID controller is used to process the speed error to generate the reference torque current keeping the magnetizing current fixed. The estimated stator flux using Recurrent Neural Network (RNN) is used to find out the rotor position. The flux angle and the reference current phasor angle are used in vector rotator to generate the reference phase currents. Hysteresis current controller block controls the switching of the 3-phase inverter to apply voltage to the motor stator. Simulation studies on different operating conditions indicate the acceptability of the drive system. The drive system only requires a speed transducer and is free from position sensor requirement. The proposed control scheme is robust under load torque disturbances and motor parameter variations. It is also simple and low cost to implement in a practical environment.

Enhancement of transient stability limit and voltage regulation with dynamic loads using robust excitation control

In stressed power systems with large induction machine component, there exist undamped electromechanical modes and unstable montonic voltage modes. This article proposes a sequential design of an excitation controller and a power system stabiliser (PSS) to stabilise the system. The operating region, with induction machines in stressed power systems, is often not captured using a linearisation around an operating point, and to alleviate this situation a robust controller is designed which guaruntees stable operation in a large region of operation. A minimax linear quadratic Gaussian design is used for the design of the supplementary control to automatic voltage regulators, and a classical PSS structure is used to damp electromechanical oscillations. The novelty of this work is in proposing a method to capture the unmodelled nonlinear dynamics as uncertainty in the design of the robust controller. Tight bounds on the uncertainty are obtained using this method which enables high-performance controllers. An IEEE benchmark test system has been used to demonstrate the performance of the designed controller

Robust nonlinear distributed controller design for active and reactive power sharing in islanded microgrids

This paper presents a robust nonlinear distributed controller design for islanded operation of microgrids in order to maintain active and reactive power balance. In this paper, microgrids are considered as inverter-dominated networks integrated with renewable energy sources (RESs) and battery energy storage systems (BESSs), where solar photovoltaic generators act as RESs and plug-in hybrid electric vehicles as BESSs to supply power into the grid. The proposed controller is designed by using partial feedback linearization and the robustness of this control scheme is ensured by considering structured uncertainties within the RESs and BESSs. An approach for modeling the uncertainties through the satisfaction of matching conditions is also provided in this paper. The proposed distributed control scheme requires information from local and neighboring generators to communicate with each other and the communication among RESs, BESSs, and control centers is developed by using the concept of the graph theory. Finally, the performance of the proposed robust controller is demonstrated on a test microgrid and simulation results indicate the superiority of the proposed scheme under different operating conditions as compared to a linear-quadratic-regulator-based controller.

Influence functions of two families of robust estimators under proportional scatter matrices

In this paper, under a proportional model, two families of robust estimates for the proportionality constants, the common principal axes and their size are discussed. The first approach is obtained by plugging robust scatter matrices on the maximum likelihood equations for normal data. A projection- pursuit and a modified projection-pursuit approach, adapted to the proportional setting, are also considered. For all families of estimates, partial influence functions are obtained and asymptotic variances are derived from them. The performance of the estimates is compared through a Monte Carlo study. © 2006 Springer-Verlag.

A second-order blind equalization method robust to ill-conditioned SIMO FIR channels

This paper deals with blind equalization of single-input-multiple-output (SIMO) finite-impulse-response (FIR) channels driven by i.i.d. signal, by exploiting the second-order statistics (SOS) of the channel outputs. Usually, SOS-based blind equalization is carried out via two stages. In Stage 1, the SIMO FIR channel is estimated using a blind identification method, such as the recently developed truncated transfer matrix (TTM) method. In Stage 2, an equalizer is derived from the estimate of the channel to recover the source signal. However, this type of two-stage approach does not give satisfactory blind equalization result if the channel is ill-conditioned, which is often encountered in practical applications. In this paper, we first show that the TTM method does not work in some situations. Then, we propose a novel SOS-based blind equalization method which can directly estimate the equalizer without knowing the channel impulse responses. The proposed method can obtain the desired equalizer even in the case that the channel is ill-conditioned. The performance of our method is illustrated by numerical simulations and compared with four benchmark methods. © 2014 Elsevier Inc.

Robust nonlinear controller design for three-phase grid-connected photovoltaic systems under structured uncertainties

This paper presents a robust nonlinear controller design for a three-phase grid-connected photovoltaic (PV) system to control the current injected into the grid and the dc-link voltage for extracting maximum power from PV units. The controller is designed based on the partial feedback linearization approach, and the robustness of the proposed control scheme is ensured by considering structured uncertainties within the PV system model. An approach for modeling the uncertainties through the satisfaction of matching conditions is provided. The superiority of the proposed robust controller is demonstrated on a test system through simulation results under different system contingencies along with changes in atmospheric conditions. From the simulation results, it is evident that the robust controller provides excellent performance under various operating conditions. © 2014 IEEE.

High-performance multifunctional graphene yarns: toward wearable all-carbon energy storage textiles

The successful commercialization of smart wearable garments is hindered by the lack of fully integrated carbon-based energy storage devices into smart wearables. Since electrodes are the active components that determine the performance of energy storage systems, it is important to rationally design and engineer hierarchical architectures atboth the nano- and macroscale that can enjoy all of the necessary requirements for a perfect electrode. Here we demonstrate a large-scale flexible fabrication of highly porous high-performance multifunctional graphene oxide (GO) and rGO fibers and yarns by taking advantage of the intrinsic soft self-assembly behavior of ultralarge graphene oxide liquid crystalline dispersions. The produced yarns, which are the only practical form of these architectures for real-life device applications, were found to be mechanically robust (Young's modulus in excess of 29 GPa) and exhibited high native electrical conductivity (2508 ± 632 S m(-1)) and exceptionally high specific surface area (2605 m(2) g(-1) before reduction and 2210 m(2) g(-1) after reduction). Furthermore, the highly porous nature of these architectures enabled us to translate the superior electrochemical properties of individual graphene sheets into practical everyday use devices with complex geometrical architectures. The as-prepared final architectures exhibited an open network structure with a continuous ion transport network, resulting in unrivaled charge storage capacity (409 F g(-1) at 1 A g(-1)) and rate capability (56 F g(-1) at 100 A g(-1)) while maintaining their strong flexible nature.

A robust approach for automated lung segmentation in thoracic CT

Lung segmentation in thoracic computed tomography (CT) scans is an important preprocessing step for computer-aided diagnosis (CAD) of lung diseases. This paper focuses on the segmentation of the lung field in thoracic CT images. Traditional lung segmentation is based on Gray level thresholding techniques, which often requires setting a threshold and is sensitive to image contrasts. In this paper, we present a fully automated method for robust and accurate lung segmentation, which includes a enhanced thresholding algorithm and a refinement scheme based on a texture-aware active contour model. In our thresholding algorithm, a histogram based image stretch technique is performed in advance to uniformly increase contrasts between areas with low Hounsfield unit (HU) values and areas with high HU in all CT images. This stretch step enables the following threshold-free segmentation, which is the Otsu algorithm with contour analysis. However, as a threshold based segmentation, it has common issues such as holes, noises and inaccurate segmentation boundaries that will cause problems in future CAD for lung disease detection. To solve these problems, a refinement technique is proposed that captures vessel structures and lung boundaries and then smooths variations via texture-aware active contour model. Experiments on 2,342 diagnosis CT images demonstrate the effectiveness of the proposed method. Performance comparison with existing methods shows the advantages of our method.

Robust network traffic classification

As a fundamental tool for network management and security, traffic classification has attracted increasing attention in recent years. A significant challenge to the robustness of classification performance comes from zero-day applications previously unknown in traffic classification systems. In this paper, we propose a new scheme of Robust statistical Traffic Classification (RTC) by combining supervised and unsupervised machine learning techniques to meet this challenge. The proposed RTC scheme has the capability of identifying the traffic of zero-day applications as well as accurately discriminating predefined application classes. In addition, we develop a new method for automating the RTC scheme parameters optimization process. The empirical study on real-world traffic data confirms the effectiveness of the proposed scheme. When zero-day applications are present, the classification performance of the new scheme is significantly better than four state-of-the-art methods: random forest, correlation-based classification, semi-supervised clustering, and one-class SVM.

Robust adaptive backstepping excitation controller design for simple power system models with external disturbances

This paper presents a nonlinear robust adaptive excitation controller design for a simple power system model where a synchronous generator is connected to an infinite bus. The proposed controller is designed to obtain the adaption laws for estimating critical parameters of synchronous generators which are considered as unknown while providing the robustness against the bounded external disturbances. The convergence of different physical quantities of a single machine infinite bus (SMIB) system, with the proposed control scheme, is ensured through the negative definiteness of the derivative of Lyapunov functions. The effects of external disturbances are considered during formulation of Lyapunov function and thus, the proposed excitation controller can ensure the stability of the SMIB system under the variation of critical parameters as well as external disturbances including noises. Finally, the performance of the proposed scheme is investigated with the inclusion of external disturbances in the SMIB system and its superiority is demonstrated through the comparison with an existing robust adaptive excitation controller. Simulation results show that the proposed scheme provides faster responses of physical quantities than the existing controller.

Construção de base organizacional e suas implicações para performance corporativa: evidências da área abastecimento do Petróleo brasileiro S.A.

Esta dissertação examina algumas implicações do processo de implementação de estratégias para a performance corporativa. Este relacionamento é examinado na Área de negócios Abastecimento, da empresa Petróleo Brasileiro S.A, durante o período de 1996 e 2003. A despeito da profusão de estudos sobre estratégia empresarial, ainda há escassez de trabalhos que examinem o processo de implementação de mudanças organizacionais e suas implicações para o aprimoramento de certos indicadores de performance corporativa. Adicionalmente, tendem a prevalecer na literatura gerencial, abordagens pontuais de caráter imediatista e prescritivo, que não captam o processo de mudança organizacional e suas implicações para performance ao longo do tempo. o exame da implementação de estratégias é realizado com base em seis variáveis organizacionais extraídas da literatura existente: "comportamento da liderança"; "interação e influência"; "inovação e aprendizado"; "gestão de pessoas"; "comunicação e fluxos de conhecimento" e "estrutura organizacional". As implicações das mudanças na base organizacional para performance corporativa são examinadas a partir de dezenove indicadores, agrupados em três categorias: (i) operacionais, (ii) econômico-financeiro e (iii) segurança, meio ambiente e saúde. Esta dissertação consiste num estudo de caso individual, o qual é baseado em evidências empíricas qualitativas e quantitativas, coletadas em trabalhos de campo. A coleta dos dados baseou-se em fontes e técnicas múltiplas. Os efeitos das variáveis organizacionais que comporiam o Abastecimento, antes da criação da Área de negócio, em 1996, foram pequenos. Esses efeitos foram moderados no período entre 1996 a 2000, só apresentando impactos relevantes sobre indicadores operacionais entre 2000 e 2003, com reflexos positivos sobre o desempenho econômico, pois muitos custos foram reduzidos. Isso sugere que estratégias tecnológicas de longo prazo são um rumo robusto e consistente. As evidências sugerem que a empresa optou pela construção de uma base organizacional visando melhoria de performance no longo prazo, alinhando-se com autores que defendem essa construção como forma de fortalecer a competitividade no longo prazo. Esta dissertação contribui para o entendimento de fatores organizacionais que favorecem a implementação de estratégias e dos mecanismos que alavancam aprendizado e inovação numa empresa nacional. Este estudo conclui que a utilização de estruturas organizacionais, com o suporte da liderança e prática de baixas barreiras interfuncionais, alavancaram o aprendizado e a inovação, favorecendo resultados econômicos. Isto contradiz a proposição de autores que afirmam que reestruturação organizacional possui baixo potencial de geração de resultados, ou que enfatizam soluções de curto prazo para obtenção imediata de resultados, em detrimento da competitividade da empresa nos médio e longo prazos.

Powerful CEOs and their impact on corporate performance

We argue in this paper that executives can only impact firm outcomes if they have influence over crucial decisions. Based on this idea we develop and test a hypothesis about how CEOs’ power to influence decisions will affect firm performance: since managers’ opinions may differ, firms whose CEOs have more decision-making power should experience more variability in firm performance. Thus performance depends on the interaction between executive characteristics and organizational variables. By focusing on this interaction we are able to use firm-level characteristics to test predictions that are related to unobservable managerial characteristics. Using such firmlevel characteristics of the Executive Office we develop a proxy for the CEO’s power to influence decisions and provide evidence consistent with our hypothesis. Firm performance (measured by Tobin’s Q, stock returns and ROA) is significantly more variable for firms with greater values of our proxy for CEO influence power. The results are robust across various tests designed to detect differences in variability.